Learning Fine-Grained Image Similarity with Deep Ranking

@article{Wang2014LearningFI,
  title={Learning Fine-Grained Image Similarity with Deep Ranking},
  author={Jiang Wang and Yang Song and Thomas Leung and Chuck Rosenberg and Jingbin Wang and James Philbin and Bo Chen and Ying Wu},
  journal={2014 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2014},
  pages={1386-1393}
}
Learning fine-grained image similarity is a challenging task. It needs to capture between-class and within-class image differences. This paper proposes a deep ranking model that employs deep learning techniques to learn similarity metric directly from images. It has higher learning capability than models based on hand-crafted features. A novel multiscale network structure has been developed to describe the images effectively. An efficient triplet sampling algorithm is also proposed to learn the… CONTINUE READING
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